Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

• MeSH
• alely MeSH
• celogenomová asociační studie MeSH
• checkpoint kinasa 1 genetika   MeSH
• checkpoint kinasa 2 genetika   MeSH
• diabetes mellitus 2. typu MeSH
• dieta MeSH
• dlouhověkost genetika   MeSH
• dospělí MeSH
• fertilita genetika   MeSH
• genetická predispozice k nemoci MeSH
• kosti a kostní tkáň metabolismus   MeSH
• lidé středního věku MeSH
• lidé MeSH
• menopauza genetika   MeSH
• myši inbrední C57BL MeSH
• myši MeSH
• ovarium metabolismus   MeSH
• předčasná menopauza genetika   MeSH
• primární ovariální insuficience genetika   MeSH
• protein FMRP genetika   MeSH
• stárnutí genetika   MeSH
• uterus MeSH
• zdravé stárnutí genetika   MeSH
• zvířata MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• myši MeSH
• ženské pohlaví MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Dálný východ MeSH
• Evropa MeSH

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.

• MeSH
• Bayesova věta MeSH
• celogenomová asociační studie * MeSH
• genetická predispozice k nemoci * MeSH
• jednonukleotidový polymorfismus * MeSH
• lidé MeSH
• lokus kvantitativního znaku * MeSH
• mapování chromozomů metody   MeSH
• nádorové biomarkery genetika   MeSH
• nádory prsu genetika   MeSH
• regulační oblasti nukleových kyselin MeSH
• rizikové faktory MeSH
• vazebná nerovnováha MeSH
• Check Tag
• lidé MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

• MeSH
• celogenomová asociační studie * MeSH
• genetická predispozice k nemoci MeSH
• lidé MeSH
• mutace MeSH
• nádory prsu genetika   patologie   MeSH
• protein BRCA1 genetika   MeSH
• studie případů a kontrol MeSH
• triple-negativní karcinom prsu genetika   patologie   MeSH
• vazebná nerovnováha MeSH
• Check Tag
• lidé MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• metaanalýza MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH
• Research Support, N.I.H., Intramural MeSH